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Transaction Fee Observations — Record Quality Audit + String Normalisation + Adjacent Row Changes
x402
Transaction Fee Observations — Record Quality Audit + String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three local analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 supplied transaction fee observation rows containing fee_units and transaction_count fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Transaction fee observations — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied transaction fee observations records (fee_units, transaction_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports derived from the supplied rows: (1) a record quality audit highlighting missing, null, or out-of-range values; (2) a string normalisation report for categorical fields like instrument_group; and (3) an adjacent row changes report showing value differences between consecutive rows for the chosen numeric field (fee_units or transaction_count). No external data is fetched; all analysis is performed locally on the submitted data.
Example use cases
Fee data quality audit before reporting
“I have 150 rows of daily transaction fee observations with instrument_group labels and fee_units values — can you run a full record quality audit, normalise the string fields, and show me any adjacent row changes for fee_units so I can clean the data before our monthly finance report?”
Detecting consecutive fee spikes
“Can you analyse these 80 transaction fee records and give me the adjacent row changes for transaction_count? I want to see where consecutive rows have big jumps so I can flag unusual activity.”
String normalisation for instrument group labels
“My fee observation dataset has messy instrument_group strings mixed with quality issues across 60 rows — please run the string normalisation and record quality audit reports on fee_units so I can standardise everything before loading it into our data warehouse.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-03-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, cost-efficient set of three data quality reports — record quality audit, string normalisation, and adjacent row changes — on transaction fee observation data (fee_units, transaction_count) in a single call for up to 200 rows. It is ideal when you want local, offline-style analysis without any live lookups or external enrichment, and when the flat $0.01 USDC cost for all three reports is preferable to calling separate single-purpose endpoints.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, instrument_group, date, fee_units, transaction_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema rejection
- Numeric values outside allowed range (-1e12 to 1e12) cause validation failure
- Empty rows array returns an error
- Payment of 0.01 USDC not provided or rejected via x402 protocol
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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